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Electric Vehicles Charging Scheduling Optimization for Total Elapsed Time Minimization
Li Ping Qian1,2; Xinyue Zhou1; Ningning Yu1; Yuan Wu3,4
2020-05
Conference Name2020 IEEE 91st Vehicular Technology Conference (VTC2020-Spring)
Source PublicationIEEE Vehicular Technology Conference
Conference Date25-28 May 2020
Conference PlaceAntwerp, Belgium
Abstract

With the rapid advancement of electric vehicle (EV) technology, EV has been emerging as a promising transportation due to the low carbon emission. However, the frequent and long time charging is indispensable to continue travelling. During peak hours, EVs further spend long time on the path routing because of the traffic congestion and queuing in the charging stations. Therefore, we study the EV charging scheduling problem that minimizes the total elapsed time which includes charging time for EVs through jointly optimizing the charging path routing and charging station selection in this paper. Considering the NP-hardness of this optimization problem, we propose an efficient EV charging scheduling method to obtain the optimal solution based on crowd sensing through considering the remaining energy in the battery, traffic condition, and the queue length of charging stations. Simulation results demonstrate that the proposed backtracking method based on crowd sensing can effectively reduce the total elapsed time, in comparison with the greedy algorithm.

KeywordBacktracking Method Crowd Sensing Electric Vehicles Matrix Decomposition Method Total Elapsed Time
DOI10.1109/VTC2020-Spring48590.2020.9128915
URLView the original
Language英語English
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Document TypeConference paper
CollectionINSTITUTE OF APPLIED PHYSICS AND MATERIALS ENGINEERING
Corresponding AuthorLi Ping Qian
Affiliation1.College of Information Engineering, Zhejiang University of Technology, Hangzhou, Zhejiang, China
2.National Mobile Communications Research Laboratory, Southeast University, Nanjing, Jiangsu, China
3.Department of Computer and Information Science, University of Macau, Macao SAR, China
4.State Key Laboratory of Internet of Things for Smart City, University of Macau, Macao SAR, China
Recommended Citation
GB/T 7714
Li Ping Qian,Xinyue Zhou,Ningning Yu,et al. Electric Vehicles Charging Scheduling Optimization for Total Elapsed Time Minimization[C],2020.
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